关键词 "family tree" 的搜索结果, 共 24 条, 只显示前 480 条
Multifamily automation for occupancy goals
Preserve memories effortlessly.
Surprise your loved ones with personalized gifts!
InternVL Family: A Pioneering Open-Source Alternative to GPT-4o. 接近GPT-4o表现的开源多模态对话模型 InternVL 家族:利用开源套件缩小与商业多模态模型的差距——GPT-4o 的先驱开源替代方案 InternVL3,一个性能强大的开源多模态大模型。其中InternVL3-78B同时在感知能力和推理能力上同时达到了开源第
A Model Context Protocol server for OpenStreetMap APIs
MCP server that provides code context and analysis for AI assistants. Extracts directory structure and code symbols using WebAssembly Tree-sitter parsers with Zero Native Dependencies.
Neutree MCP servers
MCP Server for Tree-sitter
A demo repository created using the GitHub MCP server
An mcp server that efificiently generates a node tree and related metadata for a figma node.
A template repository that includes a dev container for running a local LLM and included knowledge base. Add a git repo using `git subtree` or `git submodule` and update it using an MCP Client/Server
MCP server for analyzing WallStreetBets
An MCP server for use with LLM chatbots providing tools related to OpenStreetMap
"Zero setup" & "Blazingly fast" general code file relationship analysis. With Python & Rust. Based on tree-sitter and git analysis. Support MCP and ready for AI🤖
OpenStreetMap MCP Server Implementation
iotdb-mcp-server for tree model
Baidu AI Search combines Baidu Search Engine with LLM modesl to find best response for your query. Check detail at https://github.com/baidubce/app-builder/tree/master/python/mcp_server/ai_search and
A Model Context Protocol (MCP) server for platform-agnostic file capabilities, including advanced search/replace and directory tree traversal
An OpenStreetMap MCP server implementation that enhances LLM capabilities with location-based services and geospatial data.
Lovart 全球首个设计 Agent 体验 Lovart 的三个特点: 一、全链路设计和执行,一句话搞定 以前的文生图工具,它们所提供的任务是“生成图片”这一环。 而设计 Agent,则像一位“设计执行官”,覆盖从创意拆解到专业交付的整个视觉流程。 从意图拆解 → 任务链 → 最后成品,一句话全搞定。 单次可以执行上
Being-M0 基于业界首个百万级动作数据集 MotionLib,用创新的 MotionBook 编码技术,将动作序列转化为二维图像进行高效表示和生成。Being-M0 验证了大数据+大模型在动作生成领域的技术可行性,显著提升动作生成的多样性和语义对齐精度,实现从人体动作到多款人形机器人的高效迁移,为通用动作智能奠定基础。 Being-M0的主要功能 文本驱动动作生成:根据输入的自然语言
OpenMemory MCP 是mem0推出的基于开放模型上下文协议(MCP)构建的开源工具,能解决 AI 工具记忆痛点,实现不同工具间共享上下文信息。OpenMemory MCP支持 100% 本地运行,数据存储在用户本地设备上,确保隐私和安全。OpenMemory MCP 具备跨平台支持、标准化内存操作、集中式仪表板等优势,广泛用在软件开发、项目管理、错误跟踪等场景,帮助用户提升工作效率,让
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